Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kersken, Matthias | - |
| dc.contributor.author | Raisch, Fabian | - |
| dc.contributor.author | Male, Markus | - |
| dc.contributor.author | Tischler, Benjamin | - |
| dc.date.accessioned | 2026-06-03T06:59:43Z | - |
| dc.date.available | 2026-06-03T06:59:43Z | - |
| dc.date.issued | 2026-06 | - |
| dc.identifier.uri | https://fordatis.fraunhofer.de/handle/fordatis/486 | - |
| dc.identifier.uri | http://dx.doi.org/10.24406/fordatis/445 | - |
| dc.description.abstract | The referenced paper (https://arxiv.org/abs/2606.01994) presents the ThermBuild dataset, which comprises real-world measurements from two single-family homes and simulations of 958 TRNSYS building models. The buildings cover diverse combinations of air-source heat pump systems, numbers of thermal zones, occupancy profiles, building ages, thermal masses, sizes, orientations, window glazings, five European climates, and ventilation configurations. The dataset contains 15-minute-resolution operational data spanning 15 months for the real-world buildings and 3 years for the simulated buildings. Each building time series includes detailed measurements of heat pump operation, the heating distribution system, the domestic hot water system, weather conditions, and zone-level indoor climate variables. The ThermBuild dataset is designed for data-driven thermal dynamics modeling, thereby supporting the deployment of energy-efficient control, as well as fault detection and diagnosis in buildings. It is particularly suited for transfer learning, generalization modeling, benchmarking, simulation-to-reality transfer, and reproducible thermal modeling research. | en |
| dc.language.iso | en | en |
| dc.relation.isreferencedby | 10.48550/arXiv.2606.01994 | - |
| dc.rights.uri | https://creativecommons.org/licenses/by-sa/4.0/ | en |
| dc.subject | AI building training data | en |
| dc.subject.ddc | DDC::500 Naturwissenschaften und Mathematik::510 Mathematik::518 Numerische Analysis | en |
| dc.subject.ddc | DDC::500 Naturwissenschaften und Mathematik::530 Physik::536 Wärme | en |
| dc.subject.ddc | DDC::000 Informatik, Informationswissenschaft, allgemeine Werke::000 Informatik, Wissen, Systeme::005 Computerprogrammierung, Programme, Daten | en |
| dc.title | ThermBuild: Real-world and simulated thermal data from 960 residential multi-zone buildings in Central Europe | en |
| dc.type | Tabular Data | en |
| dc.contributor.funder | Bundesinstitut für Bau-, Stadt- und Raumforschung BBSR (Deutschland) | en |
| dc.description.technicalinformation | CSV-data table | en |
| fordatis.group | Energietechnologien und Klimaschutz | en |
| fordatis.institute | IBP Fraunhofer-Institut für Bauphysik | en |
| fordatis.project.fhgid | 11-23397-2030-00001 | en |
| fordatis.rawdata | false | en |
| fordatis.sponsorship.projectid | 10.08.18.7-24.49 | en |
| fordatis.sponsorship.projectname | Datengetriebene Modellierung von Gebäudeenergiesystemen mittels Transfer Learning | en |
| fordatis.sponsorship.projectacronym | DAMO-TL | en |
| fordatis.sponsorship.ResearchFrameworkProgramm | Innovationsprogramm ZukunftBau | en |
| fordatis.date.start | 2025-02 | - |
| fordatis.date.end | 2026-04 | - |
| Appears in Collections: | Fraunhofer-Institut für Bauphysik IBP | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| ThermBuild_measure_raw.zip | Raw measurement data | 15,09 MB | ZIP | Download/Open |
| ThermBuild_measure_Temp_raw.zip | Raw measurement data - additional room temperatures | 8,69 MB | ZIP | Download/Open |
| ThermBuild_measure_imputed.zip | Imputed measurement data - gaps filled | 15,77 MB | ZIP | Download/Open |
| ThermBuild_Sim.zip | Simulated data | 13,09 GB | ZIP | Download/Open |
| 0_Dataset_description.txt | description of data set, experimental design and simulations | 32 B | Text | Download/Open |
This item is licensed under a Creative Commons License